Bryan Goldsmith

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Bryan Goldsmith is an Assistant Professor in the Department of Chemical Engineering. His works focus on the development of novel catalysts and materials. The world is facing a growing population, mass consumerism, and rising greenhouse gas levels, all the while people strive to increase their standard of living. Computational modeling of catalysts and materials, and making use of its synergy with experiments, facilitates the process to design new systems since it provides a valuable way to test hypotheses and understand design criteria. His research team focuses on obtaining a deep understanding of catalytic systems and advanced materials for use in sustainable chemical production, pollution abatement, and energy generation. They use first-principles modeling (e.g., density-functional theory and wave function based methods), molecular simulation, and data analytics tools (e.g., statistical learning and data mining) to extract key insights of catalysts and materials under realistic conditions, and to help create a platform for their design.

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)

A computational prediction for a group of gold nanoclusters (global model) could miss patterns unique to nonplaner clusters (subgroup 1) or planar clusters (subgroup 2)

Yue Fan

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Yue Fan is an Assistant Professor in the Department of Mechanical Engineering. The primary research interest in his group is to provide a substantive knowledge on the mechanics and micro-structural evolution in complex materials systems under extreme environments via predictive modeling. In particular, they focus on describing highly disordered systems (such as glasses, grain boundaries, etc) from the perspective of potential energy landscape (PEL), and correlating materials properties with their underlying PEL structures. The ultimate goal is to facilitate the development of new science-based high performance materials with novel functions and unprecedented strength, durability, and resistance to traditional degradation and failure.

Phani Motamarri

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Phani Motamarri is an Assistant Research Scientist in the department of Mechanical Engineering. His research interests lie in the broad scope of computational materials science with emphasis on computational nano-science leading to applications in the areas of mechanics of materials and energy. His research is strongly multidisciplinary, drawing ideas from applied mathematics, data science, quantum-mechanics, solid-mechanics, materials science and scientific computing.

The current research focus lies in developing systematically improvable real-space computational methodologies and associated mathematical techniques for conducting large-scale electronic-structure (ab-initio) calculations -via- density functional theory (DFT). Massively parallel and scalable numerical algorithms using finite-elements (DFT-FE) are developed as a part of this research effort, which enabled large-scale DFT calculations on tens of thousands of atoms for the first time using finite-element basis. These computational methods will aid fundamental studies on defects in materials, molecular and nanoscale systems which otherwise would have been difficult to study with the existing state of the art computational methods. Current areas of application include — (a) first-principles modelling of energetics of point defects and dislocations in Al, Mg and its alloys which are popular in light-weighting applications to provide useful inputs to meso-scale and continuum models, (b) providing all-electron DFT input to advanced electronic structure approaches like the GW method for accurate prediction of electronic properties in semiconductor-materials.

Electron-density contours of 3430 atom aluminum nanocluster using pseudopotential DFT-FE

Electron-density contours of 3430 atom aluminum nanocluster using pseudopotential DFT-FE

Electron density contours of 3920 electron silicon nanocluster using all-electron DFT-FE

Electron density contours of 3920 electron silicon nanocluster using all-electron DFT-FE

Computational time (CPU-Hrs) per SCF iteration for the reduced-scaling subspace projection method and conventional diagonalization approach(ChFSI-FE). Case study: Alkane chains upto 7000 atoms.

Computational time (CPU-Hrs) per SCF iteration for the reduced-scaling subspace projection method and conventional diagonalization approach(ChFSI-FE). Case study: Alkane chains upto 7000 atoms.

Angela Violi

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Angela Violi is a Professor in the Department of Mechanical Engineering, and adjunct faculty in Chemical Engineering, Biophysics, Macromolecular Science and Engineering, and Applied Physics. The research in the group of Violi is focused on the application of statistical mechanics and computational methods to chemically and physically oriented problems in nanomaterials and biology. The group investigates the formation mechanisms of nanomaterials for various applications, including energy and biomedical systems, and the dynamics of biological systems and their interactions with nanomaterials.

violinanoparticlegenesis

Dominika Zgid

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Dominika Zgid is an Assistant Professor in the Department of Chemistry. Her group bridges the fields of chemistry, physics and material sciences seeking to explain and predict the electronic movement in finite molecular systems and infinite crystalline materials. They develop new theoretical approaches that will advance current theoretical tools in chemistry that can be applied to a variety of industrial applications.

Liang Qi

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Professor Qi’s research fields are investigations of the mechanical and chemical properties of materials by applying theoretical and computational tools, including first-principles calculations, atomistic simulations and multiscale modeling. His major research interests are quantitative understanding of the intrinsic electronic/atomistic mechanisms for the mechanical deformation, phase transformation and chemical degradation (corrosion/oxidation) of advanced alloys and other structural/functional materials. Currently he is focusing on the studies of deformation defects and interfaces in materials under extreme conditions, such as high stress and/or chemically active environment, where the materials behaviors and properties can be dramatically different than those predicted by classical theories and models. He is also developing the numerical methods to integrate these electronic/atomistic results with large-scale simulations and experimental characterizations in order to design materials with improved mechanical performances and chemical stabilities.

A Jahn-Teller distortion signifies the onset of the shear instability for a body-centered-cubic crystal placed under tension. The symmetry breaking correlates with the intrinsic ductility of the material, and the strain at which it appears can be controlled by alloying.

A Jahn-Teller distortion signifies the onset of the shear instability for a body-centered-cubic crystal placed under tension. The symmetry breaking correlates with the intrinsic ductility of the material, and the strain at which it appears can be controlled by alloying.

Don Siegel

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Don Siegel is an Associate Professor affiliated with the Mechanical Engineering Department and the Department of Material Science and Engineering. His research targets the discovery, characterization, and understanding of novel materials for energy-related applications. These efforts primarily employ atomic scale modeling to predict thermodynamic properties and kinetics. These data provide the necessary ingredients for identifying performance limiting mechanisms and for the “virtual screening” of candidate compounds having desired properties. Prof. Siegel is currently exploring several varieties of energy storage materials, lightweight structural alloys, and materials suitable for use in carbon capture applications.

Atomic scale model of a liquid electrolyte/solid Li2O2 interface in a Li-air battery cathode.

Atomic scale model of a liquid electrolyte/solid Li2O2 interface in a Li-air battery cathode.

Kai Sun

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His  research focuses on understanding the role of strong correction effects in many-body quantum systems. The objective is to discover novel quantum states/materials and to understand their exotic properties using theoretical/numerical methods (with emphasis on topological properties). In his research, numerical techniques are applied to resolve the fate of a quantum material (or a theoretical model) in the presence of multiple competing ground states and to provide quantitative guidance for further (experimental/theoretical) investigations.

TI Animation

Interaction induced topological insulator with spontaneously-generated orbital rotations. This figure demonstrate how to use strong interactions to generate a topological state of matter in a many-body quantum system.

Katsuyo Thornton

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Thornton’s research focuses on computational and theoretical investigations of the evolution of microstructures and nanostructures during processing and operation of materials. These investigations facilitate the understanding of the underlying physics of materials and their performance, which will aid us in designing advanced materials with desirable properties and in developing manufacturing processes that would enable their fabrication. The topics include growth and coarsening of precipitates, evolution of morphologically and topologically complex systems, microstructure-based simulations of electrochemical systems such as batteries, and self-assembly of quantum dots and other nanoscale phenomena during heteroepitaxy of semiconductors.  These projects involve advanced computational methods and large-scale simulations performed on high-performance computational platforms, and insights provide a means for material design and optimization.

A snapshot from a simulation of charge-discharge process in a lithium-ion battery, based on an experimentally obtained microstructure.

A snapshot from a simulation of charge-discharge process in a lithium-ion battery, based on an experimentally obtained microstructure.

Anthony Waas

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Anthony Waas is the Felix Pawlowski Collegiate Professor Emeritus of Aerospace Engineering and Mechanical Engineering (courtesy). The development of validated analytical and computational methods to understand how a structure (such as an air-vehicle wing, a fuselage, the load bearing structure of a land-vehicle, the wing of an insect, a wind turbine blade) made of multi-materials responds to external environments is the overarching goal of Wass’ research group. Naturally, this involves multi-physics and mechanics based models at different spatial and temporal scales. To achieve this goal, the group performs a combination of experiments, computational modeling and analysis, and theoretical developments when necessary. This work has led to novel algorithms and multi-scale methods that provide a balance between high fidelity and computational efficiency, with particular emphasis on capturing damage and failure mechanics, including interaction between these in a mesh (discretization) objective manner. Publications listed in ISI Web of Science, under the name “Waas, AM” will show the diversity of computational discovery and engineering related research that the group has done and is doing.

Crack growth prediction (code developed by Dr. Rudraa Raju)

Crack growth prediction (code developed by Dr. Rudraa Raju)